Predicting severe outcomes using national early warning score (NEWS) in patients identified by a rapid response system: a retrospective cohort study.
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ABSTRACT:
SUBMITTER: Kim SH
PROVIDER: S-EPMC8429773 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:AimsInternational early warning scores (EWS) including the additive National Early Warning Score (NEWS) and logistic EWS currently utilise physiological snapshots to predict clinical deterioration. We hypothesised that a dynamic score including vital sign trajectory would improve discriminatory power.MethodsMulticentre retrospective analysis of electronic health record data from postoperative patients admitted to cardiac surgical wards in four UK hospitals. Least absolute shrinkage and selection operator-type regression (LASSO) was used to develop a dynamic model (DyniEWS) to predict a composite adverse event of cardiac arrest, unplanned intensive care re-admission or in-hospital death within 24 h.ResultsA total of 13,319 postoperative adult cardiac patients contributed 442,461 observations of which 4234 (0.96%) adverse events in 24 h were recorded. The new dynamic model (AUC = 0.80 [95% CI 0.78-0.83], AUPRC = 0.12 [0.10-0.14]) outperforms both an updated snapshot logistic model (AUC = 0.76 [0.73-0.79], AUPRC = 0.08 [0.60-0.10]) and the additive National Early Warning Score (AUC = 0.73 [0.70-0.76], AUPRC = 0.05 [0.02-0.08]). Controlling for the false alarm rates to be at current levels using NEWS cut-offs of 5 and 7, DyniEWS delivers a 7% improvement in balanced accuracy and increased sensitivities from 41% to 54% at NEWS 5 and 18% to -30% at NEWS 7.ConclusionsUsing an advanced statistical approach, we created a model that can detect dynamic changes in risk of unplanned readmission to intensive care, cardiac arrest or in-hospital mortality and can be used in real time to risk-prioritise clinical workload.
| S-EPMC7762721 | biostudies-literature
Project description:BACKGROUND:the National Early Warning Score (NEWS) is a tool based on vital signs that aims to standardise detection of, and response to, clinical deterioration in adults. NEWS has been adopted in hospitals but not adapted for other settings. This study aimed to explore the feasibility of measuring the NEWS in care homes and describe the distribution of NEWS readings amongst care home residents. METHODS:descriptive analysis of all NEWS readings recorded in a 30-month period (2016-19) across 46 care homes in one Clinical Commissioning Group in England. Comparisons were made between measurements taken as a routine reading and those prompted by concern about acute illness. RESULTS:a total of 19,604 NEWS were recorded from 2,424 older adults (≥65 years; mean age 85). Median NEWS was 2. Two thirds (66%) of residents had a low NEWS (≤2), and 28% had a score of 0. Of the total NEWS readings, 6,277 (32%) were known to be routine readings and 2,256 (12%) were measured because of staff concerns. Median NEWS was 1 for routine and 2 for concern recordings. Overall, only 12% of NEWS were high (≥5), but a higher proportion were elevated when there were concerns about acute illness (18%), compared with routine recordings (7%). CONCLUSIONS:use of NEWS in care homes appears to be feasible. The majority of NEWS were not elevated, and the distribution of scores is consistent with other out-of-hospital settings. Further work is required to know if NEWS is triggering the most appropriate response and improving care home resident outcomes.
| S-EPMC6911654 | biostudies-literature
Project description:BACKGROUND:The national early warning score (NEWS) enables early detection of in-hospital patient deterioration and timely activation of hospital's rapid response team (RRT). NEWS was updated in 2017 to include a separate SpO2 scale for those patients with type II respiratory failure (T2RF). In this study we investigated whether NEWS with and without the new SpO2 scale for the T2RF patients is associated with immediate and in-hospital patient outcomes among the patients actually attended by the RRT. METHODS:We conducted a two-year prospective observational study including all adult RRT patients without limitations of medical treatment (LOMT) in a large Finnish university associated tertiary level hospital. According to the first vital signs measured by the RRT, we calculated NEWSs for the RRT patients and further utilized the new SpO2 scale for the patients with confirmed T2RF. We used multivariate logistic regression and area under the receiver operating characteristic analyses to test NEWS's accuracy to predict two distinct outcomes: RRT patient's I) immediate need for intensive care and/or new LOMT and 2) in-hospital death or discharge with cerebral performance category >2 and/or LOMT. RESULTS:The final cohort consisted of 886 RRT patients attended for the first time during their hospitalization. Most common reasons for RRT activation were respiratory (343, 39%) and circulatory (226, 26%) problems. Cohort's median (Q1, Q3) NEWS at RRT arrival was 8 (5, 10) and remained unchanged if the new SpO2 scale was applied for the 104 patients with confirmed T2RF. Higher NEWS was independently associated with both immediate (OR 1.28; 95% CI 1.22-1.35) and in-hospital (1.15; 1.10-1.21) adverse outcomes. Further, NEWS had fair discrimination for both the immediate (AUROC 0.73; 0.69-0.77) and in-hospital (0.68; 0.64-0.72) outcomes. Utilizing the new SpO2 scale for the patients with confirmed T2RF did not improve the discrimination capability (0.73; 0.69-0.76 and 0.68; 0.64-0.71) for these outcomes, respectively. CONCLUSIONS:We found that in patients attended by a RRT, the NEWS predicts patient's hospital outcome with moderate accuracy. We did not find any improvement using the new SpO2 scale in T2RF patients.
| S-EPMC6915867 | biostudies-literature
Project description:AimAlthough rapid response systems (RRS) are used to prevent adverse events, Japan reportedly has low activation rates and high mortality rates. The National Early Warning Score (NEWS) could provide a solution, but it has not been validated in Japan. We aimed to validate NEWS for Japanese patients.MethodsThis retrospective observational study included data of 2,255 adult patients from 33 facilities registered in the In-Hospital Emergency Registry in Japan between January 2014 and March 2018. The primary evaluated outcome was mortality rate 30 days after RRS activation. Accuracy of NEWS was analyzed with the correlation coefficient and area under the receiver operating characteristic curve. Prediction weights of NEWS parameters were then analyzed using multiple logistic regression and a machine learning method, classification and regression trees.ResultsThe correlation coefficient of NEWS for 30-day mortality rate was 0.95 (95% confidence interval [CI], 0.88-0.98) and the area under the receiver operating characteristic curve was 0.668 (95% CI, 0.642-0.693). Sensitivity and specificity values with a cut-off score of 7 were 89.8% and 45.1%, respectively. Regarding prediction values of each parameter, oxygen saturation showed the highest odds ratio of 1.36 (95% CI, 1.25-1.48), followed by altered mental status 1.23 (95% CI, 1.14-1.32), heart rate 1.21 (95% CI, 1.09-1.34), systolic blood pressure 1.12 (95% CI, 1.04-1.22), and respiratory rate 1.03 (95% CI, 1.05-1.26). Body temperature and oxygen supplementation were not significantly associated. Classification and regression trees showed oxygen saturation as the most heavily weighted parameter, followed by altered mental status and respiratory rate.ConclusionsNational Early Warning Score could stratify 30-day mortality risk following RRS activation in Japanese patients.
| S-EPMC8122242 | biostudies-literature
Project description:AimEarly identification of patients at risk of serious adverse events (SAEs) is of vital importance, yet it remains a challenging task. We investigated the predictive power of National Early Warning Score (NEWS) 2, as compared to NEWS, among patients assessed by a Rapid response team (RRT).MethodsProspective, observational cohort study on 898 consecutive patients assessed by the RRTs in 26 Swedish hospitals. For each patient, NEWS and NEWS 2 scores were uniformly calculated by the study team. The associations of NEWS and NEWS 2 scores with unanticipated admissions to Intensive care unit (ICU), mortality and in-hospital cardiac arrests (IHCA) within 24 h, and the composite of these three events were investigated using logistic regression. The predictive power of NEWS and NEWS 2 was assessed using the area under the receiver operating characteristic (AUROC) curves.ResultsThe prognostic accuracy of NEWS/NEWS 2 in predicting mortality was acceptable (AUROC 0.69/0.67). In discriminating the composite outcome and unanticipated ICU admission, both NEWS and NEWS 2 were relatively weak (AUROC 0.62/0.62 and AUROC 0.59/0.60 respectively); for IHCA the performance was poor. There were no differences between NEWS and NEWS 2 as to the predictive power.ConclusionThe prognostic accuracy of NEWS 2 to predict mortality within 24 h was acceptable. However, the prognostic accuracy of NEWS 2 to predict IHCA was poor. NEWS and NEWS 2 performed similar in predicting the risk of SAEs but their performances were not sufficient for use as a risk stratification tool in patients assessed by a RRT.
| S-EPMC8718668 | biostudies-literature
Project description:Aim of the studyThe National Early Warning Score (NEWS) is a validated method for predicting clinical deterioration in hospital wards, but its performance in prehospital settings remains controversial. Modern machine learning models may outperform traditional statistical analyses for predicting short-term mortality. Thus, we aimed to compare the mortality prediction accuracy of NEWS and random forest machine learning using prehospital vital signs.MethodsIn this retrospective study, all electronic ambulance mission reports between 2008 and 2015 in a single EMS system were collected. Adult patients (≥ 18 years) were included in the analysis. Random forest models with and without blood glucose were compared to the traditional NEWS for predicting one-day mortality. A ten-fold cross-validation method was applied to train and validate the random forest models.ResultsA total of 26,458 patients were included in the study of whom 278 (1.0%) died within one day of ambulance mission. The area under the receiver operating characteristic curve for one-day mortality was 0.836 (95% CI, 0.810-0.860) for NEWS, 0.858 (95% CI, 0.832-0.883) for a random forest trained with NEWS variables only and 0.868 (0.843-0.892) for a random forest trained with NEWS variables and blood glucose.ConclusionA random forest algorithm trained with NEWS variables was superior to traditional NEWS for predicting one-day mortality in adult prehospital patients, although the risk of selection bias must be acknowledged. The inclusion of blood glucose in the model further improved its predictive performance.
| S-EPMC8244434 | biostudies-literature
Project description:The aim of this study is to evaluate the usefulness of the pre-hospital National Early Warning Score (pNEWS) and the pre-hospital Modified Early Warning Score (pMEWS) for predicting admission and in-hospital mortality in elderly patients presenting to the emergency department (ED). We also compare the value of the pNEWS with that of the ED NEWS (eNEWS) and ED MEWS (eMEWS) for predicting admission and in-hospital mortality. This retrospective, single-centre observational study was carried out in the ED of Jikei University Kashiwa Hospital, in Chiba, Japan, from 1st April 2017 to 31st March 2018. All patients aged 65 years or older were included in this study. The pNEWS/eNEWS were derived from seven common physiological vital signs: respiratory rate, peripheral oxygen saturation, the presence of inhaled oxygen parameters, body temperature, systolic blood pressure, pulse rate and Alert, responds to Voice, responds to Pain, Unresponsive (AVPU) score, whereas the pMEWS/eMEWS were derived from six common physiological vital signs: respiratory rate, peripheral oxygen saturation, body temperature, systolic blood pressure, pulse rate and AVPU score. Discrimination was assessed by plotting the receiver operating characteristic (ROC) curve and calculating the area under the ROC curve (AUC). The median pNEWS, pMEWS, eNEWS and eMEWS were significantly higher at admission than at discharge (p < 0.001). The median pNEWS, pMEWS, eNEWS and eMEWS of non-survivors were significantly higher than those of the survivors (p < 0.001). The AUC for predicting admission was 0.559 for the pNEWS and 0.547 for the pMEWS. There was no significant difference between the AUCs of the pNEWS and the pMEWS for predicting admission (p = 0.102). The AUCs for predicting in-hospital mortality were 0.678 for the pNEWS and 0.652 for the pMEWS. There was no significant difference between the AUCs of the pNEWS and the pMEWS for predicting in-hospital mortality (p = 0.081). The AUC for predicting admission was 0.628 for the eNEWS and 0.591 for the eMEWS. The AUC of the eNEWS was significantly greater than that of the eMEWS for predicting admission (p < 0.001). The AUC for predicting in-hospital mortality was 0.789 for the eNEWS and 0.720 for the eMEWS. The AUC of the eNEWS was significantly greater than that of the eMEWS for predicting in-hospital mortality (p < 0.001). For admission and in-hospital mortality, the AUC of the eNEWS was significantly greater than that of the pNEWS (p < 0.001, p < 0.001), and the AUC of the eMEWS was significantly greater than that of the pMEWS (p < 0.01, p < 0.05). Our single-centre study has demonstrated the low utility of the pNEWS and the pMEWS as predictors of admission and in-hospital mortality in elderly patients, whereas the eNEWS and the eMEWS predicted admission and in-hospital mortality more accurately. Evidence from multicentre studies is needed before introducing pre-hospital versions of risk-scoring systems.
| S-EPMC6526008 | biostudies-literature
Project description:Backround/aimTo identify, at an early stage of intensive care, patients who will require readmission to the intensive care unit (ICU) based on their National Early Warning Score (NEWS-d) at discharge.Materials and methodsOverall, 536 patients aged >18 years who stayed at a tertiary ICU for >24 h were included. Patients who readmitted and not readmitted to the intensive care within 48 h after discharge were compared.ResultsMean patient age was 64.26 ± 18.50 years and 252 (44.7%) patients were male. Mean Acute Physiology and Chronic Health Evaluation II (APACHE II) score was 21.86 ± 8.74; mean NEWS-d was 4.48 ± 2.53. Forty-nine (9.1%) were readmitted to ICU. The reasons for initial admission, age, and NEWS-d vvalues were significantly different between the 2 groups. The NEWS-d values of the readmitted group were significantly higher (9.16 ± 1.05) than nonreadmitted group (4.01 ± 2.13). Based on receiver operation curve analysis, sensitivity and specificity were 98% and 95%, respectively, considering a NEWS-d cut-off value of 7.5 as the limit value for estimating readmission.ConclusionA NEWS-d value of >7.5 demonstrated high sensitivity and specificity in identifying the risk of readmission for patients being discharged from ICU.
| S-EPMC7491295 | biostudies-literature
Project description:IntroductionSince the introduction of the UK's National Early Warning Score (NEWS) and its modification, NEWS2, coronavirus disease 2019 (COVID-19), has caused a worldwide pandemic. NEWS and NEWS2 have good predictive abilities in patients with other infections and sepsis, however there is little evidence of their performance in COVID-19.MethodsUsing receiver-operating characteristics analyses, we used the area under the receiver operating characteristic (AUROC) curve to evaluate the performance of NEWS or NEWS2 to discriminate the combined outcome of either death or intensive care unit (ICU) admission within 24?h of a vital sign set in five cohorts (COVID-19 POSITIVE, n?=?405; COVID-19 NOT DETECTED, n?=?1716; COVID-19 NOT TESTED, n?=?2686; CONTROL 2018, n?=?6273; CONTROL 2019, n?=?6523).ResultsThe AUROC values for NEWS or NEWS2 for the combined outcome were: COVID-19 POSITIVE, 0.882 (0.868-0.895); COVID-19 NOT DETECTED, 0.875 (0.861-0.89); COVID-19 NOT TESTED, 0.876 (0.85-0.902); CONTROL 2018, 0.894 (0.884-0.904); CONTROL 2019, 0.842 (0.829-0.855).ConclusionsThe finding that NEWS or NEWS2 performance was good and similar in all five cohorts (range?=?0.842-0.894) suggests that amendments to NEWS or NEWS2, such as the addition of new covariates or the need to change the weighting of existing parameters, are unnecessary when evaluating patients with COVID-19. Our results support the national and international recommendations for the use of NEWS or NEWS2 for the assessment of acute-illness severity in patients with COVID-19.
| S-EPMC7648887 | biostudies-literature
Project description:OBJECTIVE:In hospitalized patients, the risk of sepsis-related mortality can be assessed using the quick Sepsis-related Organ Failure Assessment (qSOFA). Currently, different tools that predict deterioration such as the National Early Warning Score (NEWS) have been introduced in clinical practice in Emergency Departments (ED) worldwide. It remains ambiguous which screening tool for mortality at the ED is best. The objective of this study was to evaluate the predictive performance for mortality of two sepsis-based scores (i.e. qSOFA and Systemic Inflammatory Response Syndrome (SIRS)-criteria) compared to the more general NEWS score, in patients with suspected infection directly at presentation to the ED. METHODS:We performed a retrospective cohort study. Patients who presented to the ED between June 2012 and May 2016 with suspected sepsis in a large tertiary care center were included. Suspected sepsis was defined as initiation of intravenous antibiotics and/or collection of any culture in the ED. Outcome was defined as 10-day and 30-day mortality after ED presentation. Predictive performance was expressed as discrimination (AUC) and calibration using Hosmer-Lemeshow goodness-of-fit test. Subsequently, sensitivity, and specificity were calculated. RESULTS:In total 8,204 patients were included of whom 286 (3.5%) died within ten days and 490 (6.0%) within 30 days after presentation. NEWS had the best performance, followed by qSOFA and SIRS (10-day AUC: 0.837, 0.744, 0.646, 30-day AUC: 0.779, 0.697, 0.631). qSOFA (?2) lacked a high sensitivity versus SIRS (?2) and NEWS (?7) (28.5%, 77.2%, 68.0%), whilst entailing highest specificity versus NEWS and SIRS (93.7%, 66.5%, 37.6%). CONCLUSIONS:NEWS is more accurate in predicting 10- and 30-day mortality than qSOFA and SIRS in patients presenting to the ED with suspected sepsis.
| S-EPMC6347138 | biostudies-literature